From plant breeding to industrial process:

Integrated data management with a Research Resource Planning Mezino, Rudy

1 ; Duminil, Tristan

1 ; Royer, Romain1

1Doriane SAS, 31 av. Jean Médecin, 06000 Nice, France

Information Management Insights for Wheat breeding and Pasta Processing Quality

Durum wheat (Triticum turgidum durum) transformation sector for Pasta faces strong and diversified insights that R&D needs to address. In order to control the full process from raw matter to the final product, research departments must take into account many information. Particularly in plant R&D, genetic information, agronomic performances and processing qualities must be managed efficiently and analyzed altogether to get qualitative pastas.

As the wheat transformation sector is strongly involved into breeding, R&D organizations¹ have to deal with new insights and settle strategies and processes to give efficient responses for better seed performances and quality of the pasta transformation process.

Modern breeding techniques such as genomic and marker assisted selection, combined with high throughput phenotyping generate huge amounts of information to improve traits and resistances to environmental constraints. In addition, through GxE analysis breeders can provide industry a stable quality of pasta regarding environment variations.

To comply with the needs of the market, generated by an integrated chain of return of experience from the food industry and consumers, breeders can propose seed traits compatible with processing standards.

New relevant societal expectations for transparency also impacts breeding organizations and their information systems by requiring a fine traceability of the seeds in terms of production, genetic origin and transformation.

Therefore, data management becomes a real challenge to make this information a source of improvement in breeding.

“ R&D organizations need to […] give efficient responses for better seed

performances and quality of the pasta transformation process ”

► Real time data management from the breeding to the sales department

increases the reactivity and decision-making during field works.

► Encourage collaboration between researchers. Improves data sharing quality, and

reduces the redundancy of information to save resources and investments.

Benefits of an RRP (Research Resource Planning) for plant breeding

► Standardize and industrialize processes to improve the efficiency of the

work and save time.

► Valuation of research data lets breeders centralize and compile phenoty-

pic, genomic and environmental information and extract the best indicators.

www.doriane.com

Skilled Information System teams build integrated data management and analysis approaches, based on a Research Resource Planning² and collaborative database systems, to support innovative long-term processes such as wheat pedigree breeding, agronomic research and laboratory analysis.

The solution proposes all-in-one tools with (I) Data warehouse capacities for heterogeneous information management from multi activities (II) Process-oriented software for daily R&D work planning and monitoring (III) Data analysis tools for advanced reporting and decision making assistance.

¹ Research departments of seed companies rely on RnDExperience® to achieve their breeding objectives, such as CAUSSADE Semences and RAGT (ranked number 1 in Europe on the winter wheat market) www.doriane.com/en/success-stories

² Royer F.: Enterprise Integrated Data Management, ERP and RRP, in the Seed Business, SeedQuest (2009) : « For research departments, these ecosystems of software are replaced by RRP,

or Research Resource Planning, solutions using a shared relational database and able to manage complex business processes.

The RnDExp® software suite by Doriane is an example of RRP. »